Data Intelligence

What is the Difference Between a Data Dictionary and a Business Glossary?

Actian Corporation

November 18, 2019

In metadata management, we often talk about data dictionaries and business glossaries. Although they might sound similar, they’re quite different. Let’s take a look at their differences and relations.

What is a Data Dictionary?

A data dictionary is a collection of descriptions of data objects or items in a data model.

These descriptions can include attributes, fields, or even properties on their data, such as their types, transformations, relations, etc.

Data dictionaries help data explorers better understand their data and metadata. Usually in the form of tables or spreadsheets, data dictionaries are a must-have for IT knowledge for technical users such as developers, data analysts, data scientists, etc.

What is a Business Glossary?

While data dictionaries are useful to technical users, a business glossary is meant to bring meaning and context to data in all departments of the enterprise.

A business glossary is, therefore, a place where business and/or data terms are defined. It may sound simple, however, all employees in an organization rarely share a common understanding of even basic terms such as “contact” and “customer”.

The Main Differences Between Data Dictionaries and Business Glossaries Are:

Data dictionaries deal with database and system specifications, mostly used by IT teams. Business glossaries provide more accessible and standardized definitions for everyone in the organization.

Data dictionaries usually come in the form of schemas, tables, columns, etc. whereas a business glossary provides a unique definition for business terms in textual form.

A business glossary cross references terms and their relationships whereas data dictionaries do not.

What is the Relation Between a Data Dictionary and a Business Glossary?

The answer is simple: a business glossary provides meaning to the data dictionary.

For example, a US social security number (SSN) will be defined as “a unique number assigned by the US government for the purpose of identifying individuals within the US Social Security System” in the business glossary. In the data dictionary, the term SSN is defined as “a nine character string typically displayed with hyphens”.

If a data citizen ever has a doubt on what the term “SSN” means in the context of their data dictionary, they can always search for the associated business term inside the business glossary.

Interested in Automating a Data Dictionary and Building a Business Glossary for Your Enterprise?

Create a central metadata repository for all corporate data sources with our data catalog thanks to our connectors and APIs.

Our tool also provides a user friendly and intuitive way to build and import your business glossaries in order to link these definitions with any concepts.

Create a single source of truth in your enterprise.

About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.

Data Integration

Getting Ready to Upgrade From v9 or v10 of Actian DataConnect to v11

Pamela Fowler

November 14, 2019

If you are getting ready to upgrade from v9 or v10 to v11 of Actian DataConnect, we have put together a learning video series that can help you with the migration.

Get yourself started at https://communities.actian.com/s/getting-started-quick-tutorials.

About Pamela Fowler

Pamela Fowler is SVP - Customer Success at Actian, overseeing worldwide support infrastructure. Pamela leads strategic direction and tactical execution for customer support and managed services, ensuring high customer satisfaction. She's a champion of 'voice of the customer,' aligning feedback with Actian's operational roadmap. Pamela's blog articles highlight customer advocacy, support best practices, and service innovation. Browse her posts to learn how robust support can elevate user experiences.

Data Management

Chat With Us!

Pamela Fowler

November 13, 2019

Learn About the New Way to Engage Support Services at Actian

We are delighted to introduce the “Live Chat” feature, which was embedded in “Actian Communities” on November 11, 2019. It is a complete chat solution that enables instant chat support with Actian subject matter experts.

Each chat request will be directed to the right subject matter expert, based on the Top-Level Product you choose when initiating the chat. Note that in the chat widget, you will see only the Top-Level Products that you own, instead of a long list of all Actian products.

Answers can be delivered in real-time and a case will be automatically created with each live chat request.

The Chat Transcript will be tied to the case created via Live Chat. The transcript will contain details about the time the chat was initiated, the time it was accepted by the Actian Expert, and the actual conversation between the Actian Expert and the authenticated customer.

We believe that real-time chat will improve the customer experience and provide quicker resolutions to inquiries.

Please note this feature is only available to logged-in users. Please find the detailed documentation of Live Chat on Actian Communities in the “Learn More‘ section.

About Pamela Fowler

Actian Life

Veterans Day Employee Spotlight

Rae Coffman-Bueb

November 11, 2019

Each month, we will be featuring a different employee in our Employee Spotlight series. This series was born with the belief that your life experiences make you the unique person you are today and influence what you bring to the amazing culture here at Actian. We have chosen to feature those incredible individuals with a blog post dedicated to them.

Today, in honor of Veterans Day, we stand with our servicemen and women who have served and sacrificed in the U.S. military. At Actian, we are proud of each and every Veteran in our workforce who brings undeniable perspective, discipline, and integrity to our business. It is an honor and privilege to recognize some of Actian’s veterans in a special, Veterans Day employee spotlight.

Rosemary Ramon

Branch of Service: Navy

Rank: E5

Length of Service: 4 years

MOS: Aviation Storekeeper (AK)

Sitting in a high school assembly, Rosemary found herself being inspired by the compelling military recruiter. Filled with a sense of patriotism, she began considering joining the military. Rosemary narrowed down what branch to join between Navy and Air Force – and as an 18-year-old, since the Air Force recruiter was out to lunch, her decision was made to join the Navy.

Rosemary completed bootcamp in Chicago, IL and went to A School in Meridian, Mississippi. She ultimately was stationed in Sigonella, Sicily.

As an Aviation Storekeeper, Rosemary worked on the flight line. She was responsible for receiving repairable items from the aircraft, as well as procuring new parts so they stayed mission ready. Her favorite job though was finding lost parts, such as rotor blades and engines. That’s right, ENGINES! It apparently was much easier and common than one would think. Because they were so large, they are brought in on a forklift in a crate and the paperwork would be taped to the outside. From time to time, someone would pull the paperwork and bring it to their desk to be worked on and that is how the engine would become lost.

While in the military, Rosemary learned the value of teamwork – but more than just teamwork, it helped her see how remarkable and adaptable people are. With customers, it has transferred into being able to understand if they will be able to adjust to an integration; for employees, it translates to whether or not they are able to rise up and overcome the never ending challenges – and as long as they put their mind to it, I believe they can! “Joining the military was one of the best decisions of my life. I was able to see more of the world at that young age and it gave me a tremendous amount of perspective.”

Dean Elzey

Branch of Service: Air Force (1991) Army (1994)

Rank: O2

Length of Service: 8 years

MOS: Jet Engine Mechanic (Air Force)/ Military Intelligence Officer (Army)

Growing up the son of a Senior Master Sergeant, the possibility of enlisting was always an option. Following college, Dean decided to join the Air Force and worked happily as a Jet Engine Mechanic – the role he had dreamed of! Unfortunately, though, due to a skin reaction to the jet fuel he was constantly encountering, Dean found himself looking at alternate roles. Around that time, Dean had become eligible (AECP Grad) to become an officer, but due to the Air Force having recently merged MAC and SAC (Military Airlift Command and Strategic Airlift Command), a number of pilots were being declined positions, making it difficult to make rank. So, he was given the offer to transfer to another branch. Dean ultimately selected a position in the Army as Military Intelligence Officer for the 92^nd Rear Operations Command. The day he received his bars as an officer was one of the greatest days of his life! After receiving his bars, he fulfilled his six-year commit and transitioned into the reserves.

Dean is still influenced daily by his time in the military – primarily by the amount of discipline and structure it provided. He has learned to knock out the little stuff as fast as possible, so that more focus can be given to the big stuff. While structure is important in his personal and professional life, one of his key learnings was something he was taught by General Dan Johnson; he was told, “If you can go to work every day, and do the ordinary – whatever that is for you – you can expect extraordinary results.”

Robert Gorsuch

Branch of Service: Army

Rank: E4

Length of Service: 3 years

MOS: Helicopter Crew Chief

Growing up, Robert always knew he would join the military, as it was something of a tradition in his family. In fact, his father was a career officer that served for almost 35 years. Robert was born in Germany, as a US citizen, while his father was stationed there. Growing up in Germany, as an American expat, he was still subject to German laws including military draft for anyone graduating high school. As a dual citizen, Robert had the option of choosing between serving in either German or US military.

After completing boot camp in the US, he was stationed back home in Frankfurt, Germany. As a Helicopter Crew Chief, Robert was assigned to a small unit known as an “Air Taxi Unit” that was responsible for flying high ranking officers and visiting dignitaries throughout Europe.

Robert attributes his experience in the Army, coupled by his German heritage, to his sense of due diligence – especially when related to work and projects. During his time in the Army, it provided Robert the opportunity to enjoy his passion for aviation and travel – he even got his private pilot license. As a Sales Engineer at Actian, he is also able to enjoy his love of travel in his role.

Thank you to all the veterans across the US for their service and sacrifice.

Interested in working at Actian? Check out our open roles and apply today!

About Rae Coffman-Bueb

Rae Coffman-Bueb is Director of Employee Experience at Actian, dedicated to enhancing organizational culture. With a background in People Operations, Rae has implemented global best practices that empower teams and streamline HR processes. She provides guidance on talent development, onboarding, and cross-functional collaboration. Rae's blog posts focus on employee engagement, internal communications, and HR innovations. Check them out for tips on boosting workplace satisfaction.

Data Management

It’s Back to the Future for Flat Files – Part 2

Actian Corporation

November 11, 2019

Why Embedded Software Application Developers Loath Databases

Last week I wrote an initial blog on flat files and why embedded software application developers readily adopted them. Simply put, they’re always there – if you’ve got an operating system that’s more than a bare-bones executive kernel it’s there and it’s free. Also, flat files are really simple to use, and, while there may be underlying differences in various file formats, encryption techniques strengths, and other underlying characteristics, from a developer’s standpoint they’re the same at the API level. But, it’s the alternatives to flat files that developers are reluctant to use, first and foremost, databases.

Is Choosing Flat Files or Databases Kind of Like Choosing Between Two Political Candidates You Don’t Like?

We’re in the election season so I couldn’t resist the analogy. In answer to the question: Yes. For most developers, choosing between a flat file and a database is similar to choosing between two candidates you just rather do without. On the one hand, you’ve got Candidate A, “tried and true”, but they don’t measure up to the challenges you expect them to face going forward. On the other hand, you’ve got Candidate B, a choice who makes lots of promises, but you don’t think they can deliver, and you expect the investments to make their initiatives real to be astronomical. If you think I’m crazy enough to apply any real-life politicians to this comparison – sorry, I’m going to play politician myself and pass on that. But you get the general point (and hopefully a good chuckle).

Upon Further Inspection of the Plan, Can I Go Back and Vote for the Other Guy?

The fact is, in the past, Databases really have been Candidate B in this scenario; let me give you a bit more detail and it will be crystal clear why Developers have historically shunned them.

1. I’m a Developer Not a Database Administrator and My End-Users Are Business Analysts.

Developers know that a database will offer them more functionality than a flat file, everything from built-in indexing, networking, administrative and underlying at-rest and in-transit security, and far more. Just undertaking a do-it-yourself project for indexing or writing search and sort routines gives most developers enough of a headache to know a database offers more. However, with a flat file, all of that extra code is directly under their control and they can manage the design of it and it’s completely invisible to end-users and configurable by them before anything is ever deployed. Databases have historically needed direct and periodic management to meet the needs of their end-users and their workloads, with tuning and configuration through command-line interfaces, not embedded in programming APIs.

2. You Expect Me to Stuff This Gigantic Square Peg in This Little Round Hole?

As I mentioned in the last flat file blog, most operational technology has very limited compute resources. Although modern embedded platforms are relatively resource-rich, they are generally not capable of running your typical enterprise database which can easily be half a gigabyte to several gigabytes as a deployed footprint (obviously, this doesn’t include the application/user-created data tables, schemas, etc.). File systems management presents very little overhead, often in the tens of kilobyte ranges and there’s no additional configuration needed.

3. Am I Better Off Than I Was With the Prior Regime, at Least They Understood Me?

The size and constituency are only part of the problem, indicators of what the traditional database was designed to do and run on, namely as a relational database running in a data center, supporting either transactional operations on data in real-time or analytical operations or larger sets of data in hindsight. Most developers don’t want relational mapping, they want a simple API to directly access the data they are managing – generally, real-time but for more than discrete transactions or after-the-fact analytics. Since they’re not interested in relational mapping they’re generally also uninterested in picking up SQL skills.

Respect the Legacy, But Move Towards the Future

I get it, as I said in the last blog on flat files, I used to be one of these OT engineers myself and I hated databases but that was in the late 1980s and early 1990s. There are far more choices out there today, some of them, like Actian Zen, are purpose-built for these environments and cater to the preferences of modern developers.

Actian is the industry leader in operational data warehouse and edge data management solutions for modern businesses. With a complete set of connected solutions to help you manage data on-premises, in the cloud, and at the edge with mobile and IoT. Actian can help you develop the technical foundation needed to support true business agility.

To learn more, visit www.actian.com.

About Actian Corporation

Data Management

It’s Back to the Future for Flat Files – Part 1

Actian Corporation

November 6, 2019

File and data management concept for flat files

Why Embedded Software Application Developers Adopted Flat Files

Recently, my colleague here in Actian Product Marketing, Pradeep Bhanot, wrote a great blog on data historians in which he called for their retirement in favor of more modern databases to support time-series data processing and analytics. But, in some ways, historians are not as historic as one of the most entrenched embedded data management solutions: the flat file. In fact, I suspect that the use of flat files is far more prevalent than the use of databases or historians as a means of embedded data management. It’s hard to prove because analysts don’t track it as a separate category of data management solutions the way they do databases or say cloud data warehouses. But the reality is that they are out there; we encounter customers in our installed base as well as prospects who are actively using flat files – and not just in their older designs.

Why Did We See All the Flat File Adoption in the First Place?

If you’re a developer and you’re writing code to collect operational technology data from sensors and other edge systems, you’re probably writing your code in C, C++, C# or some other programming language that gives you direct access to data ingested from devices. For example, back in the old days when I was an engineer through inp() and outp() statements (or to really date myself through a series of registers addressed in assembly, yikes I think I’m experiencing PTSD). You quickly find that you need somewhere and some way to store the data more permanently than the temporary memory allocation within your program. The path of least resistance is a file. After all, it’s the simplest approach and almost everyone who takes any programming class or teaches it to themselves can use the file system.

Flat Files Were “Good Enough” for Traditional Embedded Data Management

While the above explains why you have the possibility of adoption, it doesn’t detail why flat files were a good solution for the times. Let me give you a couple of key reasons they were good enough:

1. The Silo of Things Meant All Data Collection Was Local

File systems store data locally which was more than sufficient for most data-embedded applications at the edge because they were purely for local use. There wasn’t a need for additional data from parallel data streams let alone fused with other types of data and shared across networks. Thus, stand-alone file systems without network data transfer were good enough. Concerns about streaming data or extract transform and load (ETL) to some other system were not a major showstopper.

2. There Wasn’t That Much Data, Data Processing, or Analytics

Until recently, most operational technology had very limited compute resources: 32-bit or 16-bit microcontrollers, sub-MB DRAM, and limited flash or EPROM memory, etc. If you don’t know these terms, put it this way, these are your father’s Oldsmobile. With limited resources available, most software was there to perform direct control of the device against a specific process, and data collected was mostly in support of that process, not the instrumentation of the process or for analytics to inform current or future operations of that process.

3. It’s My Data, I’m the Only One Using it, so Buzz Off

Software development specs? Comments, who needs comments? OT Developers are often the only parties using the software they develop and the data generated by their code is seen generally only by them and possibly a few experts in test validation on one end and service and support on the other end. Again, because the data was generated by them and for them, the need to share that data with a business analyst or data scientist back at headquarters let alone line of business would have seemed a bit far-fetched. Traditional IT and cybersecurity professionals in the data center would not be asked nor feel the need to force themselves into these projects.

Respect the Legacy, but Move Towards the Future

I get it, I used to be one of these OT engineers myself as I alluded to above. There are some advantages if you’re a software developer to starting with file systems but, with the increasingly hyperconnected world for edge devices today – aka IoT, far more resources, heck I can get a Raspberry Pi for less than a fancy real pie, and the need to share data to push business agility, innovation, and make OT more responsive and less expensive, there is a need for change. In the next installment in this series we’ll talk about why OT software developers are loathed to let go of their flat file systems and move to modern edge data management systems.

Actian is the industry leader in operational data warehouse and edge data management solutions for modern businesses. With a complete set of solutions to help you manage data on-premises, in the cloud, and at the edge with Mobile and IoT. Actian can help you develop the technical foundation needed to support true business agility. To learn more, visit www.actian.com.

About Actian Corporation

Actian Life

Mary Poppins Rocking the Actian Halloween Costume Contest

Actian Corporation

October 31, 2019

A very diverse yet joyful group of masks including Tuesday Taco, Fortune Teller, Squid, Superman, Bob Marley, Hippie, Mary Poppins, Morphsuit, Top Gun’s Maverick, Dead-Priest-Joker, Walrus, Game of Thrones Melisandre, a Slytherin, and Actian’s People Programs Manager abducted by an alien was sighted marching around the Embarcadero Place in Palo Alto, California, on Tuesday, October 29, cheering and wishing random walkers from the surrounding offices Happy Halloween.

Having completed the Halloween Parade, the crew gathered in the office to vote for the winner of this year’s costume contest. Results were tight – as photos demonstrate, all the costumes were awesome – but we were finally able to elect the top ones:

1^st place – Mary Poppins

2^nd place – Dead-Priest-Joker

3^rd place – Fortune Teller

Congratulations to the winners and Happy Halloween to everybody!

About Actian Corporation

Data Architecture

Is Now the Right Time to Modernize Your Data Warehouse?

Actian Corporation

October 29, 2019

Technology is continually changing and determining the right time to upgrade and modernize can be tricky. If you adopt new technology too soon, this may result in churn within your organization and the implementation of immature solutions that may not meet your needs. If you wait too long, you miss out on market opportunities and productivity gains that new technology can bring to your business. When it comes to data management and data warehouse solutions, right now is the best time to move forward on modernization.

Legacy Data Warehouse Systems are Aging

If you are using an on-premises data warehouse solution, your data center hardware and storage solutions require continual monitoring, maintenance, and upgrades. Also, this equipment might be reaching the end of its serviceable life. Replacing this infrastructure requires costly capital investment and possibly locking yourself into legacy/on-premises solutions for the next 5 -10 years.

With the rapid pace of business and technology change, do you really want to lock yourself into a legacy solution for that long? Cloud-based infrastructure is more cost-effective, scalable, and flexible, enabling you to establish a new and modern data foundation to support your company’s evolving needs.

Modern Data Warehouse Solutions are Mainstream Tech

Many companies are wary of being early adopters of new technology. Vendors tend to over-sell and under-deliver their solutions, and bugs and feature deficiencies can offset new/emerging technical capabilities. Cloud-based data warehouse solutions have emerged from the early growth stage and have now normalized into stable and reliable mainstream technology suitable for supporting businesses large and small. Data warehouses like Actian Data Platform are available on-premises, on multiple cloud environments including Azure and AWS, giving companies choices in their cloud strategy.

Data warehousing and analytics aren’t just about the warehouse. You also need to get data into and out of the data warehouse easily. Integration solutions like Actian DataConnect provide the tools to manage the connections and the flow of data between your business systems and existing platforms and your cloud data warehouse solution. This integrated approach allows you to be able to modernize both your core warehouse platform and data integration strategy at the same time.

Flexibility to Adjust Capacity to Minimize Waste

One of the biggest challenges of legacy data warehouses was the need to pre-purchase capacity to support peak business processing and then have those resources be under-utilized most of the time. This happens because compute capacity varies based on business seasonality. Storage capacity is continuously growing. A modern data warehouse solution enables you to separate your compute and storage capabilities.

Allowing you to optimize capacity based on actual utilization to control costs and avoid wasted resources. Your finance leaders will like this because it saves the company money. Your business users will like it because it means they can get an extra boost of capacity whenever they need it.

Modern Data Warehouses Enable Analytics for Digital Business Processes

Digital transformation of business processes has been a leading trend in the IT industry for the past few years. As companies embrace new technology-enabled ways of working, many are finding their data analytics capabilities are woefully lacking. New data warehouse platforms can help you develop the rich, enterprise-scale, real-time analytics, and information insights that digital business processes demand.

From the flexible ingestion of data, sourced from across the enterprise to distributed data processing and robust data feeds to fuel analytics and reporting – modern hybrid data warehouses are designed for high-speed, high-performance data processing. If you aren’t moving to a modern data platform, your digital transformation efforts may be at risk over the next few years.

Finding the right time to upgrade and modernize any core IT system requires careful consideration of many factors – technical risk, business need, operational disruption, and foregone opportunities. When it comes to a data warehouse, now is the perfect time to move forward with modernization, and the experts at Actian can help. Actian offers a full suite of modern data management solutions, from cloud-based data warehouse solutions to IPaaS solutions that enable you to integrate data across your enterprise.

Learn Modernization Best Practices From Industry Experts and Insiders

Watch our on-demand webinars featuring leading industry analysts and former executives from Teradata and Netezza to learn modernization best practices.

About Actian Corporation

Data Integration

IPaaS is Key to Accelerating Innovation

Actian Corporation

October 28, 2019

Your business is evolving quickly with new competitors, changing customer needs, and the continuous refinement of both your business processes and product/service offerings to make the best of market opportunities. Sustainable competitive advantage in this environment is built on three things – information, innovation, and agility.

Your leaders understand this, which is why they are placing so much pressure on IT and business groups to accelerate digital transformation to leverage technology in new ways and deploy modern capabilities like Integrated Platform as a Service (IPaaS) to support this rapidly changing environment.

At the heart of business innovation and agility is information – more specifically, the ability to integrate analyze, and harvest information into actionable insights that help leaders to understand their environment and continuously refine business operations. The information that leaders need comes from all over your company – sales, finance, manufacturing, customer service, marketing, and others. This information is captured, stored, and managed in a wide variety of IT systems. Some of these may be hosted on-premises in your IT data centers, and others may be SaaS applications or systems managed by suppliers and partners.

Regardless of what IT systems you have, where they are located, or who manages them, the data they contain provides critical insights into opportunities, challenges, and risks that could impact your business’s performance. If you want to be successful, you need to bring your enterprise data together and get those insights in front of the decision-makers in real-time so that it can be translated into business value and competitive advantage.

That’s where Integration Platform as a Service comes in. IPaaS provides the tools and capabilities to manage all your company’s data connections in one place – giving you access to data from across the company. Individual business systems may come and go (that’s okay). IPaaS enables you to innovate within individual business functions without losing enterprise data transparency.

The proliferation of SaaS solutions and specialized off-the-shelf software from 3^rd parties over the past few years is providing business users with a vibrant marketplace of technical capabilities that they can quickly adopt and begin leveraging. All it takes is little more than the swipe of a credit card and the creation of an online profile. If a better capability is found, users simply abandon the system they were using and start using something new.

In the modern era of technology, software (and hardware) have become disposable resources, and it is data that has evolved into the durable strategic asset that companies are seeking to capture, manage and convert into a competitive advantage. IPaaS solutions like Actian DataConnect are designed to help your IT organization enable the business innovation and agility that users require while at the same time supporting the enterprise’s need for data continuity and end-to-end information insights.

The key to innovation and business agility is enabling change to take place in a safe and controlled manner – you don’t want to slow down change, only minimize disruption. IPaaS solutions provide five key capabilities that your IT organization needs to support business agility:

Centralized management of data connections and credentials.
Data flow orchestration.
Data governance and access control.
Ease of use.
Rapid time to value.

By managing these things in a centralized place, your business processes, analytics, and individual IT systems can be isolated from the impacts of individual application of platform changes. The system as a whole can continue operating while one or more pieces are being evolved. This is powerful because it means your entire business can be transformed into a platform of innovation.

You can try out new things with lower risk, and if they work, migrate off old systems and processes. If they don’t work, you can unplug the test system, capture lessons learned, and try something different.

You may have hundreds or thousands of IT systems, but you only have one company, and IPaaS gives you the tools to manage your enterprise data better. Don’t slow down business innovation – enable and encourage it with the right set of tools to enable change to happen faster, easier, and safer.

Actian can help with industry-leading IPaaS capabilities in Actian DataConnect, combined with a modern cloud data warehouse solution, Actian Data Platform. To learn more, visit DataConnect.

About Actian Corporation

Data Platform

Optimizing Cloud Compute and Data Storage for Data Analytics

Actian Corporation

October 24, 2019

When architecting your data warehouse solution, separating compute and data storage is extremely important for both operational sustainability and economic efficiency. Different things drive the technical needs for each of these, the capacity demands of the organization are different, and the best solution requires optimizing compute and data storage separately.

Data Storage Capacity is a Function of Time

The amount of data storage that your company needs is directly related to the number of business activities you’re doing. As you conduct business, you generate data – data about your customers, your products, your sales, etc. Over time, the amount of data volume your company has will grow. In busy times, the growth rate may be faster than in slow times, but the volume is always increasing. Taking this growth into account is essential when you are architecting your storage solution because the cost is directly related to data volume.

For on-premises data storage, you will need to acquire capacity in advance, based on projected data storage needs. For cloud-based storage solutions that are billed based on utilization, you will need to project your cost growth over time.

Compute Capacity is Driven by Business Trends

Compute capacity for analytics solutions is only partially influenced by the volume of data you are analyzing. The more significant factor at play is the demand for data consumption – during peak business times, the demand is higher, and during slow times, the demand is lower. Consider the example of black Friday in retail. Business activity spikes, and the demand for analytics about the business activities spike too. A couple of months later, in early January, retail sales slowed, and there was also less demand for analytics. Whether you are talking about retail sales, the launch of a new product/service, or quarter-end financial close, every business has seasonality trends that cause their demand for compute capacity to vary significantly.

For on-premises compute solutions, capacity must be purchased and reserved to accommodate peak performance loads. That means that during slow periods, there is excess capacity. For cloud-based compute solutions where billing is based on utilization, capacity can be scaled up during peak periods and scaled back down during slow periods.

Developing a Hybrid Demand Forecast is Nearly Impossible

The capacity and performance requirements for both compute and data storage environments vary over time based on the activities of the business. The demand curves for each of these solutions look very different from the other, making cost and capacity modeling based on a combined architecture is both difficult and inefficient. Rather than invest the time and resources on-demand and cost forecasting, most companies find it much easier to separate compute and data storage into separate solutions with independent cost models and demand forecasts.

Technology is Changing

Cloud-based technology capabilities are improving and changing at a tremendous pace. When it comes to data analytics and cloud data warehousing, not only is the technology getting better every day, but certain areas are evolving faster than others. For example, the density of cloud-based storage solutions is causing the per-unit cost of data storage to decline in alignment with the deployment of new hardware by cloud service providers. Compute capabilities in the cloud are improving in both capacity/scale with new distributed compute architectures, and in speed/performance with new hardware. While a company may decide to forego a storage upgrade due to the migration costs, leveraging newer compute capabilities may be advantageous.

Separating compute and data storage solutions give companies greater flexibility in upgrading parts of their architecture while leaving other parts alone. When it comes to data analytics, there are a lot of moving parts. Data volumes are increasing. Analytics and compute demands (both performance and capacity) are going up and down with business trends. Developing and executing on an accurate forecast is nearly impossible. All the while, the technology is continuously evolving and the business is demanding better economic performance from IT investments. Companies that are thriving in this environment know that keeping solutions simple and maintaining the highest level of technical flexibility is the key to success. Separating compute and data storage is an essential part of giving you the most options to optimize the data analytics on which your company depends.

Actian Data Platform on Azure provides the flexibility organizations need to optimize the ratio of compute and data storage to meet the performance objectives of the application. Learn more about the Actian Data Platform at www.actian.com/data-platform

Learn Modernization Best Practices From Industry Experts and Insiders

If you are thinking about modernizing your enterprise data warehouse, watch our on-demand webinars featuring leading industry analysts and former executives from Teradata and Netezza.

About Actian Corporation

Product Launches

Actian Data Platform on Microsoft Azure

Emma McGrattan

October 21, 2019

Today we are excited to announce the release of Actian Data Platform on Microsoft Azure. Azure is growing significantly as a platform in the enterprise space and becoming the de facto choice for retail analytics. Hence, making Actian Data Platform available on Microsoft Azure has been a priority for us.

With this release, Actian Data Platform is now available on Microsoft Azure, AWS, and on-premises, delivering on our hybrid and multi-cloud vision. We have added new features to this release, like independent scaling of compute and storage resources. This is particularly appealing to those customers who have large amounts of data which is growing quickly but may not need compute to scale at the same pace. In addition, it will also benefit customers with known compute peaks like retail experiences during holidays or during promotional periods.

True Platform That Analyzes Data Where it Naturally Resides

With the addition of Microsoft Azure, Actian’s customers now have another choice as to where they deploy their analytics. For those with data lakes that span multiple clouds and on-premises, Actian provides a unifying solution that brings analytics to all of that data from a single pane of glass. When we engage with prospects, they typically tell us that they wish to simplify their data ecosystem and bring the analytics capabilities to the data, rather than duplicating all of their data assets in a cloud data warehouse environment. Our approach is not only simpler and cheaper, it also offers greater security.

High-Performing Analytics That Thrives Under Demanding Scenarios

Actian has a long history of delivering record-breaking analytics performance, and Actian Data Platform on Azure is no different. It offers significant performance advantages over the competition and that advantage grows with data volumes, user volumes and query complexity. Actian Data Platform is designed to support large numbers of concurrent users and when you couple this with the fact that query execution times can be measured in milliseconds, it’s the ideal platform for organizations that wish to equip every business decision-maker in the organization with access to all of the data required to make the most informed decision possible.

The Actian Data Platform’s ability to handle mixed workloads means that data discovery, ad-hoc querying, batch reporting, and real-time data updates can all be happening simultaneously without the need to reconfigure the environment for each different use case and without any one of these use cases feeling the impact of the others.

Try Actian Data Platform With Your Data

You can try out Actian Data Platform and experience for yourself the high performing engine of Actian Data Platform. I’d love to hear your feedback, so don’t be shy!

About Emma McGrattan

Emma McGrattan is CTO at Actian, leading global R&D in high-performance analytics, data management, and integration. With over two decades at Actian, Emma holds multiple patents in data technologies and has been instrumental in driving innovation for mission-critical applications. She is a recognized authority, frequently speaking at industry conferences like Strata Data, and she's published technical papers on modern analytics. In her Actian blog posts, Emma tackles performance optimization, hybrid cloud architectures, and advanced analytics strategies. Explore her top articles to unlock data-driven success.

Data Platform

Getting Started With Actian Data Platform on Azure

Actian Corporation

October 21, 2019

Actian Data Platform (formerly Avalanche) on  Microsoft Azure launched this week.  This post will walk you through getting set up on Actian Data Platform on Azure. You must first have an Actian account as a customer of Actian.

After you log in to the Actian service, you will see the below screen in the center of the Actian console:

actian console

To create your first warehouse, click the green Create your first Cluster button, which will load the below screen to get you set up:

actian data platform warehouse cluster

All fields depicted above are required fields. After filling in the name of your cluster and location (e.g. East US for where your cluster will be located), you will also need to provide what size cluster you would like to create and enter an IP address to allow access.

For the cluster size, Actian uses Avalanche Units (AU) to specify the size of your warehouse. AUs are a representation of the cluster’s size, so 2AUs would be a small cluster, and 4AUs would be a larger cluster. Actian offers up to 128AU clusters. AU size of the cluster is not directly linked to the data storage size; your data storage will scale independently of the compute for the cluster. If you are using a trial, Actian recommends using a 2AU cluster to get started, as larger clusters have higher costs. Since the a is associated with a specified amount of credits, a 2AU cluster will provide the maximum amount of time for you to work with Actian.

For the IP address field, if you will be connecting to the cluster from your current location, you can click the Allow List Application IP(s) field, and a small box will pop up that states Use my IP – if you select that box, your IP will auto-populate into the IP address field. The IP address that needs to be added on the Allow List is the IP address that you will be using to connect to the Actian cluster via ODBC, JDBC, or .Net applications.

Once you are done with filling in the fields, click on the Create Cluster button. You will then be taken to the main dashboard and see the status of your cluster as Creating.

custom cluster actian data platform

After the instance is provisioned, which will take about 10-15 minutes, the Creating indicator will change to Running as shown below:

creating cluster actian data platform

The Actian cluster is now available to connect to and perform some of the following activities: loading data, performing ad-hoc querying, using BI tools such as Power BI or Tableau for reporting, or loading data into a Spark cluster or into a Data Science workbench.

To get started on your journey to connect to Actian for Azure, you will need to:

Set a connection password in the Actian web interface.
- On the Actian main console, identify the cluster whose password you want to change.
- From the cluster’s Manage menu, select Set Connection Password.
- The Set/Update Connection Password dialog opens:

connection password actian data platform

- - Enter and confirm the password for the dbuser user.
  - Click Set Connection Password.
  - The connection password is now in effect.
Download a JDBC or Actian client runtime package.
- To download drivers for Actian, log in to the web console and click the Driver & Tools link, which opens Electronic Software Delivery (ESD) in a new browser tab.

drivers and tools actian data platform

- The following download packages are available from the RELEASE dropdown for Actian.
  - Actian JDBC (for any platform): includes the JDBC driver to connect to Actian from JDBC applications. To download and install this package, see Download the Actian JDBC Package.
  - Actian Client Runtime: includes the JDBC driver, ODBC driver, and the Actian SQL Command Line Interface (CLI). To download and install this package, see Download the Actian Client Runtime Package.
- If you download an RPM package, you must install as root.
To connect from your favorite BI tools such as Power BI, Tableau, Looker, or your favorite SQL tools such as DBeaver and Squirrel SQL, or an application that uses ODBC/JDBC, you will need information specific to the application to connect. To get the information required, navigate to the cluster that you would like to connect to, and select the Manage menu and then select the Connect button.
After pressing the Connect button, a dialog will appear on-screen that provides the connection details.

The connection string can be copied via the copy button on the right of the connection string field. Once copied, the string can be pasted into the tool you plan to connect to Actian after the Actian driver is installed and connected.
For more details on how to install the driver for an example application such as DBeaver, please refer to the following how-to link: Install DBeaver and Set Up an Actian Data Platform Driver guide.

The cluster will have sample data available to use for running SQL commands or building visualizations for your favorite query tools. For SQL commands, you can find a set of sample commands here.

If you have additional questions on getting set up with Actian, please feel free to reach out to the support team.

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